According to the 2010 to 2011 Annual Directory and Statistical Report of the American Public Power Association, in the US, there is a total of 3,269 different electricity utility providers. Each utility provider has its own pricing strategy, and each customer may have a different schedule structure based on the type of application or building being supplied with electricity. For an end user, it is therefore increasingly difficult to deduce the amount of money that has to be paid for a particular period, such as a month, before they receive the respective electricity bill.
One way of estimating an amount to be paid at the end of a period is to assume that the billed amount remains more or less the same for each period. However, such an assumption is often incorrect, as the amount of energy used varies based on different external factors, such as holiday periods or weather conditions. Another approach in estimating the amount to be paid is to monitor the current energy consumption, for example using a so-called smart metering device, and then estimate the billing amount based on the energy consumption. However, this approach relies on detailed information about the energy profile used for billing the customer. Often, such energy profile information is only available in textual form in the end user's contract. However, extracting this information in order to convert an amount of energy used into an amount to be paid in terms of money for the used electricity is very user unfriendly and unreliable.
Accordingly, there is a need for better methods and systems for identifying a energy profile of an end user and estimating energy consumption charges of an end user.